The Application Of VaR Model To Risk Management Of Index Futures

These days, financial risks exist in financial market everywhere. Once thefinancial risks happen, they often bring huge economical losses. The riskmeasurement has become a very important issue to risk management in financialmarket. It has great theoretical and practical significance to study on it. The riskmeasure theory has been improved and developed continuously in the practice.With the VaR method widely used in the financial modeling, the accuracy is verycrucial to VaR measurement. The characteristics of financial return rate are the corecontent to all financial models, the traditional VaR estimation methods generallymake some assumptions that the return obey the assumed distribution in advance,but a large number of empirical studies show that the actual rate of returndistribution is not obey assumptions to distribution. We make use of the extremevalue theory and trimmed linear moment to describe the characteristics of the returndistributions, it solves problem that moment estimation cannot describe thecharacteristics of the thick tail, and apply it to study the risk in Chinese stock market.In addition, from the perspective of the High frequency data, We also make use ofthe Cornish-Fisher method to fit the real distribution, and we apply realized volatilityto Cornish-Fisher VaR estimation.This paper applies the GEV model and GPD model separately to carry on theanalysis of real example to the risk in the futures market of index of our country andcarries on the data analysis with R and EViews software. Through the analysis of realexample, the paper draws a conclusion that the fitting result of GPD model isobviously superior to that of GEV model.